Artificial Bee Colony based Approach for Web Information Retrieval | ||
| Engineering and Technology Journal | ||
| Article 6, Volume 32, 5B, May 2014, Pages 899-909 PDF (333.55 K) | ||
| DOI: 10.30684/etj.32.5B.7 | ||
| Authors | ||
| Hasanen S. Abdullah; Mustafa J. Hadi | ||
| Abstract | ||
| With the tremendous growth of information in the web, the classic query processing approaches are unable to respond to queries in real time. The aim of this paper is to develop an innovative tool using swarm intelligence to address information retrieval in the context of response time and solution quality through cope with the complexity induced by that huge volume of information. In this paper, we will show that our proposed approach that use of Artificial Bee Colony (ABC) algorithm called MABC can be another alternative to palliate the complexity issue in terms of response time while it produces a solution quality is relatively convergent or even better. Experimental tests have been conducted on two well-known CACM and NPL collections. Both are different in size, CACM is small while NPL is relatively large. Numerical results exhibit the superiority and the benefit gained from using the MABC approach instead of the classic approaches. | ||
| Keywords | ||
| Web Information Retrieval; swarm intelligence; Artificial Bee Colony; MABC; Classic Approaches | ||
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